PCOMPBIOL-D-26-00725

Prolines in Linkers of Multi-Domain Proteins: Intrinsic Regulators of Misfolding and Aggregation

PLOS Computational Biology

Dear Dr. Levy,

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Academic Editor

PLOS Computational Biology

Nir Ben-Tal

Section Editor

PLOS Computational Biology

Additional Editor Comments:

The manuscript is well received by the reviewers, with some modest and minor concerns raised. I will greatly appreciate a revised manuscript with all points satisfactorily addressed.

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1) Please ensure that the CRediT author contributions listed for every co-author are completed accurately and in full.

At this stage, the following Authors/Authors require contributions: Simona Manasra, and Yaakov Koby Levy. Please ensure that the full contributions of each author are acknowledged in the "Add/Edit/Remove Authors" section of our submission form.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Authors:

Please note here if the review is uploaded as an attachment.

Reviewer #1: Attached

Reviewer #2: This study looks at the distribution of proline clusters in protein linkers. Prolines are unusual, since they have an atypical side chain that restricts mobility. In the current study, a bioinformatic analysis is applied to identify if there are preferences for proline stretches, which may be linked to properties of co-translational folding. The main finding is that proline stretches tend to be positioned in linkers that follow domains that have complex folds. These complex folds are likely to be slow-forming, which can make them prone to aggregation. By encoding polyproline segments after these domains, the protein sequence essentially encodes a pause in translation, which can allow for folding to occur before translating subsequent domains. I have some minor comments and questions that should be addressed prior to publication.

1) There are many typos. These should be corrected.

2) Page 8 indicates that "isolated" prolines are those that do not have another proline within two residues. Does this mean the a sequence PXP would not be considered "isolated"? As written, it seems like an arbitrary criterion that PXXP would be isolated, but PXP would not. Please clarify the rationale for this choice.

3) page 12 indicates that residues are considered to be in contact if the CA atoms are within 6 Å. Why were CA distances used to identify contacts, rather than using atom-based identification? Also, 6Å seems very short for CA atoms. Wouldn't this basically limit the analysis to backbone-backbone contacts, which could potentially lead to significant changes in results. It is recommended that an atom-based contact measure be used, or perhaps just a longer CA-CA cutoff. The results may be robust. But, if they are sensitive to this choice, it would be important to understand why.

4 ) Page 13 states "to compare how disorder-promoting residues, such as proline and glycine...". Proline is thought to be more rigid, not more flexible, than a typical residue. With this in mind, it is not clear what is intended by the term "disorder-promoting"

5) page 14 states "the upstream domain i exerts the primary influence". I don't think "exerts" is appropriate at this point, as it would imply some form of causality, which I don't think is the intention of the authors.

6) The final results section "Proline clustering emerges in aggregation contexts" is not as convincing as the preceding sections. Figure 8B is described as exhibiting a correlation, but the correlation is quite weak. Figures 8C and 8D also show very weak trends. It is not clear if these minor differences are meaningful, even if they are technically statistically distinct. Connecting these differences to biological impact would be helpful.

Reviewer #3: In this manuscript, Manasra and Levy performed a proteome-wide analysis of proline organization in inter-domain linkers of multi-domain proteins. They report that clustered and consecutive prolines are enriched in linkers, particularly downstream of domains with high relative contact order, and suggest that such proline clusters may serve as intrinsic sequence-encoded pauses that facilitate co-translational folding and reduce misfolding or aggregation. The authors further show that linkers with enriched proline clusters are often adjacent to aggregation-prone domains and exhibit certain evolutionary conservation patterns. Overall, the manuscript is well written, and presents an interesting hypothesis and several potentially valuable observations, but the current evidence remains largely correlative. Several major issues should be addressed.

1. The main conclusion that proline clusters act as intrinsic regulators of co-translational folding and aggregation is not directly supported. The current data show correlations between proline clustering and domain/linker properties, but they do not establish a causal role. The title, abstract, and discussion should be toned down accordingly.

2. The definition of “clustered prolines” is broader than experimentally established ribosome-stalling motifs. Prolines separated by up to two non-proline residues may not necessarily induce translational pausing. The authors should analyze specific motif classes separately, such as PP, PPP, XPPX, PXP, and PXXP motifs.

3. The aggregation analysis is interesting but does not demonstrate an anti-aggregation function. The authors show that linkers with high proline-clustering Z-scores tend to flank domains with higher predicted aggregation scores. However, this does not prove that the proline clusters suppress aggregation. Aggregation-prone domains may belong to specific structural or functional classes that also differ in RCO, domain length, β-content, or linker disorder. The authors should avoid concluding that proline clusters reduce aggregation unless additional validation is provided.

4. The Z-score analysis is problematic for short linkers, yet short linkers are central to the proposed mechanism. The authors state that Z-scores are not informative for short linkers, but they also argue that proline enrichment in short linkers downstream of high-RCO domains is especially important for providing translational pauses. A more appropriate null model for short linkers should be used.

5. Additional negative controls are needed to demonstrate proline specificity. Glycine alone is not a sufficient control. The authors should analyze other residue clusters, such as serine/threonine-rich, charged, glutamine/asparagine-rich, or general low-complexity regions. This would help determine whether the observed patterns are specific to proline clustering or reflect general properties of disordered linkers.

6. A biologically relevant case study would greatly strengthen the manuscript. Tau is an obvious example because it contains a well-known proline-rich region adjacent to the aggregation-prone microtubule-binding repeat region. The authors could map isolated, clustered, and consecutive prolines along Tau, compare the proline-clustering profile with predicted aggregation propensity, and test whether the proline-rich region is positioned in a way consistent with their proposed anti-aggregation or spacer model.

Minor comments:

1. The authors should report effect sizes and confidence intervals, not only very small p values.

2. The threshold RCO > 0.15 should be justified, and the robustness of the conclusions to alternative thresholds should be tested.

3. AlphaFold-derived structures should be quality-controlled, for example by pLDDT filtering, before calculating contact order.

4. The Pfam-based linker definition may misclassify unannotated structured regions, coiled coils, repeat regions, or functional low-complexity domains as linkers. This limitation should be discussed.

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Reviewer #1: Yes

Reviewer #2: None

Reviewer #3: None

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

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Dear Dr. Levy,

We are pleased to inform you that your manuscript 'Prolines in Linkers of Multi-Domain Proteins: Intrinsic Regulators of Misfolding and Aggregation' has been provisionally accepted for publication in PLOS Computational Biology.

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Best regards,

Jianhan Chen, Ph.D.

Academic Editor

PLOS Computational Biology

Nir Ben-Tal

Section Editor

PLOS Computational Biology

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